Modalities of Post-Rhinoplasty Edema and Ecchymosis Measurement: A Systematic Review
Bibliographic record
Abstract
Background: Post-rhinoplasty edema and ecchymosis can influence patient satisfaction with surgery as well as result in poor quality of life. Methods to quantify such edema and ecchymosis have been described in the literature. Despite this, there is currently no collective understanding of which methods are the most effective. Hence, this systematic review aims to describe and analyze the literature on post-rhinoplasty edema and ecchymosis measurement techniques. Methods: Standard bibliographic databases (OVID Medline, EMBASE, and PubMed) were searched from their inception to December 2019 for the terms: "rhinoplasty", "postoperative", "edema", and "ecchymosis". Descriptive analysis was completed. Results: The search revealed 1116 articles of which 33 met inclusion criteria and were included for qualitative synthesis. A total of 1801 patients from all studies were included. Of the 33 included studies, there were 57 unique ecchymosis/edema measurements. The majority of studies measured edema/ecchymosis on post-operative day 1, 2, 3 and 7. Ninety-three percent of measurements described were taken subjectively from a human rater. Other techniques described included magnetic resonance imaging, ultrasound, 3-dimensional imaging, and digital analysis. Less than half of the subjective ecchymosis/edema gradings were completed by a blinded rater. Conclusion: There are a wide variety of post-rhinoplasty edema and ecchymosis techniques being used by rhinoplasty surgeons. The majority of post-rhinoplasty edema and ecchymosis measurements are completed by unblinded subjective raters. It is important that facial plastic surgeons select an accurate measurement tool so they may be able to initiate precise patient-specific management of edema and ecchymosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".